Triple
T36705409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lipayran |
E906344
|
entity |
| Predicate | hasCommonOccupation |
—
|
GENERATED |
| Object | fisher |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonOccupation Context triple: [Lipayran, hasCommonOccupation, fisher]
-
A.
isCommonInProfession
Indicates that something frequently occurs, appears, or is typical within a given profession or occupational field.
-
B.
hasTypicalOccupation
chosen
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
C.
hasOccupationCombination
Indicates that an entity holds multiple occupations or job roles in combination.
-
D.
hasOccupationInWork
Indicates that an entity holds or performs a specific occupation within a particular work, project, or creative production.
-
E.
hasOccupationRelative
Indicates that one entity has another entity as a relative who holds a particular occupation or job.
- F. None of above.
Provenance (1 batch)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:12 p.m.